The United States National Highway Traffic Safety Administration, NHTSA, has recognized that earlier generation airbag systems designed to enhance safety and vehicle seat belt restraint systems can potentially cause injury during a crash scenario especially when the occupants are not properly situated within the vehicle and/or restrained by a seat belt. As such, the NHTSA allowed automotive manufacturers the option to reduce the inflation power or aggressiveness of the first generation airbags to lessen the likelihood of an airbag related injury. These less powerful airbags are typically known as “de-powered” airbags and have been in most vehicles since 1997.
As an added precaution, the NHTSA required manufacturers to introduce an “advanced frontal airbag” which is designed to meet the needs of the occupant in a variety of specific crash scenarios. The advanced airbag systems automatically determine if and with what level of power the driver frontal airbag and the passenger frontal airbag will inflate. The appropriate level of power is generally based upon sensor inputs that can typically detect: 1) occupant size, 2) seat position, 3) seat belt use of the occupant, and 4) crash severity. Advance frontal airbags were generally designed to reduce the risk of airbag induced injury to children and adults of small stature. All passenger cars and light trucks produced after Sep. 1, 2006 in the United States are required to have the advanced frontal airbag system.
Various occupant-detection devices are known to communicate with a controller of the advanced frontal airbag system requiring the system to take appropriate action(s) (i.e. disabling the airbag in a crash). A weight-based occupant-detection system is one such device that utilizes a bladder installed in a passenger-side seat that senses weight distribution in the seat. A microcontroller in the device uses an algorithm to analyze the weight distribution and determine if the occupant may be injured by the airbag. Unfortunately, the weight-based devices are generally not designed to detect if an occupant is out of position. Yet further, such devices are not capable of differentiating between an empty seat with an inanimate object and a seat with a child. Consequently, during a crash scenario, a passenger frontal airbag could actuate without need.
Visual or imaging based systems are known that measure various features of at least one image, establish confidence levels and fuse the features together to compute an “occupant type” which in-turn is used to, for instance, enable or disable a vehicle airbag. Such a system is disclosed in U.S. Patent Application Publication 2003/0204384 A1, published Oct. 30, 2003 and incorporated herein in its entirety. Such features include an edge density taken from a single image, a wavelet feature taken from a single image, and a disparity feature that requires “stereo” images from two independent cameras. A sub-classifier of each feature independently assigns a confidence value to each one of five occupant classifications known to be: rear-facing infant seat; front-facing infant seat; adult; out of position adult; and empty seat. The fifteen class confidences are then input into a fusion classifier that is trained to intelligently combine the confidences to form a final airbag enable/disable decision.
Unfortunately, the five classification system is limited and does not include other categories such as “a child inside of an at-risk-zone” or “a child outside of an at-risk-zone” which could further refine airbag safety. Moreover, known software algorithms used to classify the three known features are likely to become confused between categories if required to handle the additional two classifications. Furthermore, additional classifications will increase the size of the neural network making training of the network more difficult. Therefore, more efficient and more effective features and methods to fulfill the seven-category-classification task are desired.